Data Engineer

Requirements:

• Strong execution knowledge of Data Modeling, Databases in general (SQL and NoSQL), software development lifecycle and practices, unit testing, functional programming, etc.
• Working knowledge of ETL and/or orchestration tools like IICS, Medallion, Airflow, Azure Data Factory, AWS Glue, GCP Composer, etc.
• Working knowledge of one or more data warehouses like Snowflake, Redshift, Hive, BigQuery, etc.
• Proficient in Spark and can optimize Spark jobs with ease.
• Proficient in at least one programming language used in data engineering, such as Python (Non-negotiable) and Scala/Rust/Java
• Understanding of the Medallion architecture pattern
• Has strong SQL knowledge along with optimisation skills
• Strong problem-solving skills with an ability to assess the financial impact of decisions, both in running the delivery team and delivering solutions to clients.
• Proficient in written and verbal communication and able to hold conversations with mid-management-level clients.
• Ability to recognise pragmatic alternatives to a perfect solution and get the delivery teams on board to pursue them, balancing time priorities with potential business impact.
• Strong people skills, including conflict resolution, empathy, communication, listening, and negotiation.
• Shows proficiency in providing technical guidance and providing leadership and mentorship to the delivery team.
• Self-driven with a strong sense of ownership.

Skills

Airflow, Data Engineering, ETL, IICS, Java, Python, Rust, SQL, Scala, Spark